adaptive mpc design -凯发k8网页登录

adaptive control of nonlinear plant by updating internal plant model at run time

adaptive mpc controllers adjust their prediction model at run time to compensate for nonlinear or time-varying plant characteristics. to implement adaptive mpc, first design a traditional model predictive controller for the nominal operating conditions of your control system, and then update the plant model and nominal conditions used by the mpc controller at run time. for more information, see . after updating, the plant model and nominal conditions remain constant over the prediction horizon.

if you can predict how the plant and nominal conditions vary in the future, you can use time-varying mpc to specify a model that changes over the prediction horizon. such a linear time-varying model is useful when controlling periodic systems or nonlinear systems that are linearized around a time-varying nominal trajectory. for more information, see .

functions

	compute optimal control with prediction model updating
	option set for `mpcmove` function
	mpc controller state

blocks

simulate adaptive and time-varying model predictive controllers

topics

adaptive mpc

to control strongly nonlinear or time-varying systems, you can use adaptive mpc to update the controller internal model for changing operating conditions.
update the internal model of an adaptive mpc controller by linearizing the nonlinear plant at each control interval.
update the internal model of an adaptive mpc controller by estimating a plant model at each control interval.
update the internal model of an adaptive mpc controller using an lpv model of the plant dynamics.

time-varying mpc

if you can predict how the plant and nominal conditions vary in the future, you can use time-varying mpc to specify a model that changes over the prediction horizon.
achieve better performance when controlling a time-varying plant by using a prediction model and nominal conditions that vary over the prediction horizon.
control an inverted pendulum in an unstable equilibrium position using a linear time-varying model predictive controller.

online model updating

to implement adaptive mpc, you must update the plant model and nominal conditions used by the mpc controller at run time.

case studies

use adaptive mpc to make a vehicle follow a reference velocity and avoid obstacles by updating the plant model and linear mixed input/output constraints at run time.